{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,16]],"date-time":"2026-06-16T09:05:14Z","timestamp":1781600714195,"version":"3.54.5"},"reference-count":49,"publisher":"Oxford University Press (OUP)","issue":"2","license":[{"start":{"date-parts":[[2025,3,13]],"date-time":"2025-03-13T00:00:00Z","timestamp":1741824000000},"content-version":"vor","delay-in-days":12,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100002341","name":"Academy of Finland","doi-asserted-by":"publisher","award":["334790"],"award-info":[{"award-number":["334790"]}],"id":[{"id":"10.13039\/501100002341","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100002341","name":"Academy of Finland","doi-asserted-by":"publisher","award":["339421"],"award-info":[{"award-number":["339421"]}],"id":[{"id":"10.13039\/501100002341","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100002341","name":"Academy of Finland","doi-asserted-by":"publisher","award":["345802"],"award-info":[{"award-number":["345802"]}],"id":[{"id":"10.13039\/501100002341","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100002341","name":"Academy of Finland","doi-asserted-by":"publisher","award":["326238"],"award-info":[{"award-number":["326238"]}],"id":[{"id":"10.13039\/501100002341","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100002341","name":"Academy of Finland","doi-asserted-by":"publisher","award":["340141"],"award-info":[{"award-number":["340141"]}],"id":[{"id":"10.13039\/501100002341","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100002341","name":"Academy of Finland","doi-asserted-by":"publisher","award":["344698"],"award-info":[{"award-number":["344698"]}],"id":[{"id":"10.13039\/501100002341","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100002341","name":"Academy of Finland","doi-asserted-by":"publisher","award":["345803"],"award-info":[{"award-number":["345803"]}],"id":[{"id":"10.13039\/501100002341","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Global Programme by Finnish Ministry of Education and Culture"},{"name":"Norwegian Health Authority South-East","award":["2020026"],"award-info":[{"award-number":["2020026"]}]},{"name":"Norwegian Health Authority South-East","award":["2023105"],"award-info":[{"award-number":["2023105"]}]},{"DOI":"10.13039\/100008730","name":"Norwegian Cancer Society","doi-asserted-by":"publisher","award":["216104"],"award-info":[{"award-number":["216104"]}],"id":[{"id":"10.13039\/100008730","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100008730","name":"Norwegian Cancer Society","doi-asserted-by":"publisher","award":["273810"],"award-info":[{"award-number":["273810"]}],"id":[{"id":"10.13039\/100008730","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Cancer Society of Finland, and the Sigrid Jus\u00e9lius Foundation"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,3,4]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Drug combinations are required to treat advanced cancers and other complex diseases. Compared with monotherapy, combination treatments can enhance efficacy and reduce toxicity by lowering the doses of single drugs\u2014and there especially synergistic combinations are of interest. Since drug combination screening experiments are costly and time-consuming, reliable machine learning models are needed for prioritizing potential combinations for further studies. Most of the current machine learning models are based on scalar-valued approaches, which predict individual response values or synergy scores for drug combinations. We take a functional output prediction approach, in which full, continuous dose-response combination surfaces are predicted for each drug combination on the cell lines. We investigate the predictive power of the recently proposed comboKR method, which is based on a powerful input\u2013output kernel regression technique and functional modeling of the response surface. In this work, we develop a scaled-up formulation of the comboKR, which also implements improved modeling choices: we (1) incorporate new modeling choices for the output drug combination response surfaces to the comboKR framework, and (2) propose a projected gradient descent method to solve the challenging pre-image problem that is traditionally solved with simple candidate set approaches. We provide thorough experimental analysis of comboKR 2.0 with three real-word datasets within various challenging experimental settings, including cases where drugs or cell lines have not been encountered in the training data. Our comparison with synergy score prediction methods further highlights the relevance of dose-response prediction approaches, instead of relying on simple scoring methods.<\/jats:p>","DOI":"10.1093\/bib\/bbaf099","type":"journal-article","created":{"date-parts":[[2025,2,25]],"date-time":"2025-02-25T07:37:42Z","timestamp":1740469062000},"source":"Crossref","is-referenced-by-count":5,"title":["Scaling up drug combination surface prediction"],"prefix":"10.1093","volume":"26","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7821-0313","authenticated-orcid":false,"given":"Riikka","family":"Huusari","sequence":"first","affiliation":[{"name":"Department of Computer Science , Aalto University, Otakaari 1B, FI-00076 Espoo,","place":["Finland"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0642-7235","authenticated-orcid":false,"given":"Tianduanyi","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Computer Science , Aalto University, Otakaari 1B, FI-00076 Espoo,","place":["Finland"]},{"name":"Institute for Molecular Medicine Finland (FIMM) , HiLIFE, University of Helsinki, Tukholmankatu 8, FI-00270 Helsinki,","place":["Finland"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1469-2215","authenticated-orcid":false,"given":"Sandor","family":"Szedmak","sequence":"additional","affiliation":[{"name":"Department of Computer Science , Aalto University, Otakaari 1B, FI-00076 Espoo,","place":["Finland"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-7806-8277","authenticated-orcid":false,"given":"Diogo","family":"Dias","sequence":"additional","affiliation":[{"name":"Institute for Molecular Medicine Finland (FIMM) , HiLIFE, University of Helsinki, Tukholmankatu 8, FI-00270 Helsinki,","place":["Finland"]},{"name":"Hematology Research Unit , University of Helsinki and Helsinki University Hospital, Haartmaninkatu 8, FI-00290 Helsinki,","place":["Finland"]},{"name":"Translational Immunology Research Program , University of Helsinki, Haartmaninkatu 8, FI-00290 Helsinki,","place":["Finland"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0886-9769","authenticated-orcid":false,"given":"Tero","family":"Aittokallio","sequence":"additional","affiliation":[{"name":"Institute for Molecular Medicine Finland (FIMM) , HiLIFE, University of Helsinki, Tukholmankatu 8, FI-00270 Helsinki,","place":["Finland"]},{"name":"Department of Cancer Genetics , Institute for Cancer Research, Oslo University Hospital, Ullernchausseen 70, N-0379 Oslo,","place":["Norway"]},{"name":"Oslo Centre for Biostatistics and Epidemiology (OCBE) , Faculty of Medicine, University of Oslo, Sognsvannsveien 9, N-0372 Oslo,","place":["Norway"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0705-4314","authenticated-orcid":false,"given":"Juho","family":"Rousu","sequence":"additional","affiliation":[{"name":"Department of Computer Science , Aalto University, Otakaari 1B, FI-00076 Espoo,","place":["Finland"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2025,3,13]]},"reference":[{"key":"2025031309021932000_ref1","doi-asserted-by":"publisher","first-page":"4265","DOI":"10.1021\/acs.jmedchem.8b01610","article-title":"A survey of the structures of us fda approved combination drugs","volume":"62","author":"Das","year":"2019","journal-title":"J Med Chem"},{"key":"2025031309021932000_ref2","doi-asserted-by":"publisher","first-page":"915","DOI":"10.1016\/j.trecan.2022.06.009","article-title":"Drug independence and the curability of cancer by combination chemotherapy","volume":"8","author":"Pomeroy","year":"2022","journal-title":"Trends in Cancer"},{"key":"2025031309021932000_ref3","doi-asserted-by":"publisher","first-page":"606","DOI":"10.1158\/2159-8290.CD-21-0212","article-title":"Independent drug action in combination therapy: Implications for precision oncology","volume":"12","author":"Plana","year":"2022","journal-title":"Cancer Discov"},{"key":"2025031309021932000_ref4","doi-asserted-by":"crossref","first-page":"74","DOI":"10.1038\/s41597-024-02915-y","article-title":"Optimizing drug combination and mechanism analysis based on risk pathway crosstalk in pan cancer","volume":"11","author":"Congxue","year":"2024","journal-title":"Scientific Data"},{"key":"2025031309021932000_ref5","doi-asserted-by":"publisher","first-page":"30830","DOI":"10.18632\/oncotarget.8306","article-title":"Prediction of mycoplasma hominis proteins targeting in mitochondria and cytoplasm of host cells and their implication in prostate cancer etiology","volume":"8","author":"Khan","year":"2016","journal-title":"Oncotarget"},{"key":"2025031309021932000_ref6","doi-asserted-by":"publisher","first-page":"10805","DOI":"10.1007\/s13277-016-4970-9","article-title":"Computational prediction of mycoplasma hominis proteins targeting in nucleus of host cell and their implication in prostate cancer etiology","volume":"37","author":"Khan","year":"2016","journal-title":"Tumor Biology"},{"key":"2025031309021932000_ref7","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0148530","article-title":"Systems biology approaches for the prediction of possible role of chlamydia pneumoniae proteins in the etiology of lung cancer","volume":"11","author":"Khan","year":"2016","journal-title":"PloS One"},{"key":"2025031309021932000_ref8","doi-asserted-by":"crossref","first-page":"7214","DOI":"10.7150\/jca.63517","article-title":"Decipher the helicobacter pylori protein targeting in the nucleus of host cell and their implications in gallbladder cancer: An insilico approach","volume":"12","author":"Wang","year":"2021","journal-title":"J Cancer"},{"key":"2025031309021932000_ref9","doi-asserted-by":"publisher","first-page":"102","DOI":"10.1016\/j.coph.2018.07.008","article-title":"Recent advances in combinatorial drug screening and synergy scoring","volume":"42","author":"Pemovska","year":"2018","journal-title":"Curr Opin Pharmacol"},{"key":"2025031309021932000_ref10","doi-asserted-by":"publisher","first-page":"3564","DOI":"10.1158\/0008-5472.CAN-17-0489","article-title":"The national cancer institute almanac: A comprehensive screening resource for the detection of anticancer drug pairs with enhanced therapeutic activitynci almanac of approved cancer drug combinations","volume":"77","author":"Holbeck","year":"2017","journal-title":"Cancer Res"},{"key":"2025031309021932000_ref11","doi-asserted-by":"publisher","first-page":"166","DOI":"10.1038\/s41586-022-04437-2","article-title":"Effective drug combinations in breast, colon and pancreatic cancer cells","volume":"603","author":"Jaaks","year":"2022","journal-title":"Nature"},{"key":"2025031309021932000_ref12","doi-asserted-by":"crossref","first-page":"3830","DOI":"10.1038\/s41467-023-39528-9","article-title":"A landscape of response to drug combinations in non-small cell lung cancer","volume":"14","author":"Nair","year":"2023","journal-title":"Nat Commun"},{"key":"2025031309021932000_ref13","doi-asserted-by":"crossref","first-page":"24","DOI":"10.1016\/j.coisb.2017.05.005","article-title":"Prediction of synergistic drug combinations","volume":"4","author":"Weinstein","year":"2017","journal-title":"Current Opinion in Systems Biology"},{"key":"2025031309021932000_ref14","doi-asserted-by":"publisher","DOI":"10.1093\/bib\/bbab355","article-title":"Machine learning methods, databases and tools for drug combination prediction","volume":"23","author":"Lianlian","year":"2021","journal-title":"Brief Bioinform"},{"key":"2025031309021932000_ref15","doi-asserted-by":"publisher","DOI":"10.1093\/bib\/bbac075","article-title":"A review of machine learning approaches for drug synergy prediction in cancer","volume":"23","author":"Torkamannia","year":"2022","journal-title":"Brief Bioinform"},{"key":"2025031309021932000_ref16","doi-asserted-by":"publisher","DOI":"10.1016\/j.drudis.2023.103625","article-title":"The recent progress of deep-learning-based in silico prediction of drug combination","volume":"28","author":"Liu","year":"2023","journal-title":"Drug Discov Today"},{"key":"2025031309021932000_ref17","doi-asserted-by":"publisher","first-page":"1538","DOI":"10.1093\/bioinformatics\/btx806","article-title":"Deepsynergy: Predicting anti-cancer drug synergy with deep learning","volume":"34","author":"Preuer","year":"2018","journal-title":"Bioinformatics"},{"key":"2025031309021932000_ref18","doi-asserted-by":"crossref","first-page":"2334","DOI":"10.1109\/TCBB.2021.3086702","article-title":"Matchmaker: A deep learning framework for drug synergy prediction","volume":"19","author":"Kuru","year":"2021","journal-title":"IEEE\/ACM Trans Comput Biol Bioinform"},{"key":"2025031309021932000_ref19","doi-asserted-by":"publisher","first-page":"568","DOI":"10.1038\/s42256-019-0122-4","article-title":"Prediction of drug combination effects with a minimal set of experiments","volume":"1","author":"Ianevski","year":"2019","journal-title":"Nature machine intelligence"},{"key":"2025031309021932000_ref20","doi-asserted-by":"publisher","first-page":"6136","DOI":"10.1038\/s41467-020-19950-z","article-title":"Leveraging multi-way interactions for systematic prediction of pre-clinical drug combination effects","volume":"11","author":"Julkunen","year":"2020","journal-title":"Nat Commun"},{"key":"2025031309021932000_ref21","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-020-19563-6","article-title":"Computationally predicting clinical drug combination efficacy with cancer cell line screens and independent drug action","volume":"11","author":"Ling","year":"2020","journal-title":"Nat Commun"},{"key":"2025031309021932000_ref22","doi-asserted-by":"crossref","first-page":"708815","DOI":"10.3389\/fbinf.2021.708815","article-title":"Predicting the effects of drug combinations using probabilistic matrix factorization","volume":"1","author":"Nafshi","year":"2021","journal-title":"Frontiers in Bioinformatics"},{"key":"2025031309021932000_ref23","doi-asserted-by":"crossref","first-page":"i93","DOI":"10.1093\/bioinformatics\/btab308","article-title":"Modeling drug combination effects via latent tensor reconstruction","volume":"37","author":"Wang","year":"2021","journal-title":"Bioinformatics"},{"key":"2025031309021932000_ref24","doi-asserted-by":"publisher","first-page":"93","DOI":"10.1016\/S0031-6997(25)00026-2","article-title":"What is synergy?","volume":"41","author":"Berenbaum","year":"1989","journal-title":"Pharmacol Rev"},{"key":"2025031309021932000_ref25","doi-asserted-by":"publisher","first-page":"585","DOI":"10.1111\/j.1744-7348.1939.tb06990.x","article-title":"The toxicity of poisons applied jointly 1","volume":"26","author":"Bliss","year":"1939","journal-title":"Annals of applied biology"},{"key":"2025031309021932000_ref26","first-page":"285","article-title":"The problem of synergism and antagonism of combined drugs","volume":"3","author":"Loewe","year":"1953","journal-title":"Arzneimittelforschung"},{"key":"2025031309021932000_ref27","doi-asserted-by":"publisher","first-page":"2286","DOI":"10.1016\/j.drudis.2019.09.002","article-title":"Applying synergy metrics to combination screening data: Agreements, disagreements and pitfalls","volume":"24","author":"Vlot","year":"2019","journal-title":"Drug Discov Today"},{"key":"2025031309021932000_ref28","doi-asserted-by":"crossref","first-page":"161","DOI":"10.1186\/s12859-023-05256-6","article-title":"Dose\u2013response prediction for in-vitro drug combination datasets: A probabilistic approach","volume":"24","author":"R\u00f8nneberg","year":"2023","journal-title":"BMC bioinformatics"},{"key":"2025031309021932000_ref29","doi-asserted-by":"publisher","DOI":"10.1038\/s44386-024-00004-z","article-title":"Predicting drug combination response surfaces","volume":"2","author":"Huusari","journal-title":"npj Drug Discovery"},{"key":"2025031309021932000_ref30","first-page":"np","article-title":"Input output kernel regression: Supervised and semi-supervised structured output prediction with operator-valued kernels","volume":"17","author":"Brouard","year":"2016","journal-title":"JMLR"},{"key":"2025031309021932000_ref31","doi-asserted-by":"publisher","first-page":"i28","DOI":"10.1093\/bioinformatics\/btw246","article-title":"Fast metabolite identification with input output kernel regression","volume":"32","author":"Brouard","year":"2016","journal-title":"Bioinformatics"},{"key":"2025031309021932000_ref32","first-page":"471","article-title":"A generalized kernel approach to structured output learning","volume-title":"ICML","author":"Kadri","year":"2013"},{"key":"2025031309021932000_ref33","doi-asserted-by":"publisher","first-page":"1000","DOI":"10.1109\/72.788641","article-title":"Input space versus feature space in kernel-based methods","volume":"10","author":"Scholkopf","year":"1999","journal-title":"IEEE Trans Neural Netw"},{"key":"2025031309021932000_ref34","article-title":"Kernel dependency estimation","volume":"15","author":"Weston","year":"2002","journal-title":"Advances in neural information processing systems"},{"key":"2025031309021932000_ref35","first-page":"510","article-title":"The matrix cookbook","volume":"7","author":"Petersen","year":"2008","journal-title":"Technical University of Denmark"},{"key":"2025031309021932000_ref36","doi-asserted-by":"publisher","first-page":"3374","DOI":"10.1109\/TNNLS.2017.2727545","article-title":"Fast kronecker product kernel methods via generalized vec trick","volume":"29","author":"Airola","year":"2017","journal-title":"IEEE transactions on neural networks and learning systems"},{"key":"2025031309021932000_ref37","doi-asserted-by":"publisher","first-page":"543","DOI":"10.1007\/s10994-021-06127-y","article-title":"Generalized vec trick for fast learning of pairwise kernel models","volume":"111","author":"Viljanen","year":"2022","journal-title":"Machine Learning"},{"key":"2025031309021932000_ref38","first-page":"1","article-title":"Rlscore: Regularized least-squares learners","volume":"17","author":"Pahikkala","year":"2016","journal-title":"Journal of Machine Learning Research"},{"key":"2025031309021932000_ref39","doi-asserted-by":"publisher","first-page":"1155","DOI":"10.1158\/1535-7163.MCT-15-0843","article-title":"An unbiased oncology compound screen to identify novel combination strategies","volume":"15","author":"O\u2019Neil","year":"2016","journal-title":"Mol Cancer Ther"},{"key":"2025031309021932000_ref40","doi-asserted-by":"publisher","first-page":"564","DOI":"10.1016\/j.cell.2017.06.010","article-title":"Defining a cancer dependency map","volume":"170","author":"Tsherniak","year":"2017","journal-title":"Cell"},{"key":"2025031309021932000_ref41","doi-asserted-by":"crossref","first-page":"25523","DOI":"10.1038\/srep25523","article-title":"Braid: A unifying paradigm for the analysis of combined drug action","volume":"6","author":"Twarog","year":"2016","journal-title":"Sci Rep"},{"key":"2025031309021932000_ref42","first-page":"iv","article-title":"The possible effects of the aggregation of the molecules of hemoglobin on its dissociation curves","volume":"40","author":"Hill","year":"1910","journal-title":"J Physiol"},{"key":"2025031309021932000_ref43","doi-asserted-by":"publisher","first-page":"633","DOI":"10.1111\/j.1472-8206.2008.00633.x","article-title":"The hill equation: A review of its capabilities in pharmacological modelling","volume":"22","author":"Goutelle","year":"2008","journal-title":"Fundam Clin Pharmacol"},{"key":"2025031309021932000_ref44","article-title":"A solution for large scale nonlinear regression with high rank and degree at constant memory complexity via latent tensor reconstruction","author":"Szedmak","year":"2020"},{"key":"2025031309021932000_ref45","doi-asserted-by":"publisher","DOI":"10.1186\/s12859-024-05789-4","article-title":"Protein function prediction through multi-view multi-label latent tensor reconstruction","volume":"25","author":"Armah-Sekum","year":"2024","journal-title":"BMC bioinformatics"},{"key":"2025031309021932000_ref46","doi-asserted-by":"publisher","first-page":"504","DOI":"10.1016\/j.csbj.2015.09.001","article-title":"Searching for drug synergy in complex dose\u2013response landscapes using an interaction potency model","volume":"13","author":"Yadav","year":"2015","journal-title":"Comput Struct Biotechnol J"},{"key":"2025031309021932000_ref47","doi-asserted-by":"publisher","first-page":"2807","DOI":"10.1016\/j.csbj.2022.05.055","article-title":"Systematic review of computational methods for drug combination prediction","volume":"20","author":"Kong","year":"2022","journal-title":"Comput Struct Biotechnol J"},{"key":"2025031309021932000_ref48","doi-asserted-by":"publisher","first-page":"97","DOI":"10.1016\/j.cels.2019.01.003","article-title":"Quantifying drug combination synergy along potency and efficacy axes","volume":"8","author":"Meyer","year":"2019","journal-title":"Cell systems"},{"key":"2025031309021932000_ref49","doi-asserted-by":"publisher","first-page":"10524","DOI":"10.1038\/s41598-022-13469-7","article-title":"Modeling synergistic effects by using general hill-type response surfaces describing drug interactions","volume":"12","author":"Schindler","year":"2022","journal-title":"Sci Rep"}],"container-title":["Briefings in Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/bib\/article-pdf\/26\/2\/bbaf099\/62397908\/bbaf099.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bib\/article-pdf\/26\/2\/bbaf099\/62397908\/bbaf099.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,3,13]],"date-time":"2025-03-13T05:02:45Z","timestamp":1741842165000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/bib\/article\/doi\/10.1093\/bib\/bbaf099\/8074755"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,3]]},"references-count":49,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2025,3,4]]}},"URL":"https:\/\/doi.org\/10.1093\/bib\/bbaf099","relation":{"has-preprint":[{"id-type":"doi","id":"10.1101\/2024.12.24.630218","asserted-by":"object"}]},"ISSN":["1467-5463","1477-4054"],"issn-type":[{"value":"1467-5463","type":"print"},{"value":"1477-4054","type":"electronic"}],"subject":[],"published-other":{"date-parts":[[2025,3]]},"published":{"date-parts":[[2025,3]]},"article-number":"bbaf099"}}